Scalable hardware architecture for disparity map computation and object location in real-time
Autor(a) principal: | |
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Data de Publicação: | 2016 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://repositorio.inesctec.pt/handle/123456789/5546 http://dx.doi.org/10.1007/s11554-013-0338-1 |
Resumo: | We present the disparity map computation core of a hardware system for isolating foreground objects in stereoscopic video streams. The operation is based on the computation of dense disparity maps using block-matching algorithms and two well-known metrics: sum of absolute differences and Census transform. Two sets of disparity maps are computed by taking each of the images as reference so that a consistency check can be performed to identify occluded pixels and eliminate spurious foreground pixels. Taking advantage of parallelism, the proposed architecture is highly scalable and provides numerous degrees of adjustment to different application needs, performance levels and resource usage. A version of the system for 640 x 480 images and a maximum disparity of 135 pixels was implemented in a system based on a Xilinx Virtex II-Pro FPGA and two cameras with a frame rate of 25 fps (less than the maximum supported frame rate of 40 fps on this platform). Implementation of the same system on a Virtex-5 FPGA is estimated to achieve 80 fps, while a version with increased parallelism is estimated to run at 140 fps (which corresponds to the calculation of more than 5.9 x 10(9) disparity-pixels per second). |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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7160 |
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Scalable hardware architecture for disparity map computation and object location in real-timeWe present the disparity map computation core of a hardware system for isolating foreground objects in stereoscopic video streams. The operation is based on the computation of dense disparity maps using block-matching algorithms and two well-known metrics: sum of absolute differences and Census transform. Two sets of disparity maps are computed by taking each of the images as reference so that a consistency check can be performed to identify occluded pixels and eliminate spurious foreground pixels. Taking advantage of parallelism, the proposed architecture is highly scalable and provides numerous degrees of adjustment to different application needs, performance levels and resource usage. A version of the system for 640 x 480 images and a maximum disparity of 135 pixels was implemented in a system based on a Xilinx Virtex II-Pro FPGA and two cameras with a frame rate of 25 fps (less than the maximum supported frame rate of 40 fps on this platform). Implementation of the same system on a Virtex-5 FPGA is estimated to achieve 80 fps, while a version with increased parallelism is estimated to run at 140 fps (which corresponds to the calculation of more than 5.9 x 10(9) disparity-pixels per second).2018-01-05T16:20:56Z2016-01-01T00:00:00Z2016info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://repositorio.inesctec.pt/handle/123456789/5546http://dx.doi.org/10.1007/s11554-013-0338-1engSantos,PMJoão Canas FerreiraJosé Silva Matosinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-05-15T10:20:11Zoai:repositorio.inesctec.pt:123456789/5546Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T17:52:46.965704Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Scalable hardware architecture for disparity map computation and object location in real-time |
title |
Scalable hardware architecture for disparity map computation and object location in real-time |
spellingShingle |
Scalable hardware architecture for disparity map computation and object location in real-time Santos,PM |
title_short |
Scalable hardware architecture for disparity map computation and object location in real-time |
title_full |
Scalable hardware architecture for disparity map computation and object location in real-time |
title_fullStr |
Scalable hardware architecture for disparity map computation and object location in real-time |
title_full_unstemmed |
Scalable hardware architecture for disparity map computation and object location in real-time |
title_sort |
Scalable hardware architecture for disparity map computation and object location in real-time |
author |
Santos,PM |
author_facet |
Santos,PM João Canas Ferreira José Silva Matos |
author_role |
author |
author2 |
João Canas Ferreira José Silva Matos |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Santos,PM João Canas Ferreira José Silva Matos |
description |
We present the disparity map computation core of a hardware system for isolating foreground objects in stereoscopic video streams. The operation is based on the computation of dense disparity maps using block-matching algorithms and two well-known metrics: sum of absolute differences and Census transform. Two sets of disparity maps are computed by taking each of the images as reference so that a consistency check can be performed to identify occluded pixels and eliminate spurious foreground pixels. Taking advantage of parallelism, the proposed architecture is highly scalable and provides numerous degrees of adjustment to different application needs, performance levels and resource usage. A version of the system for 640 x 480 images and a maximum disparity of 135 pixels was implemented in a system based on a Xilinx Virtex II-Pro FPGA and two cameras with a frame rate of 25 fps (less than the maximum supported frame rate of 40 fps on this platform). Implementation of the same system on a Virtex-5 FPGA is estimated to achieve 80 fps, while a version with increased parallelism is estimated to run at 140 fps (which corresponds to the calculation of more than 5.9 x 10(9) disparity-pixels per second). |
publishDate |
2016 |
dc.date.none.fl_str_mv |
2016-01-01T00:00:00Z 2016 2018-01-05T16:20:56Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://repositorio.inesctec.pt/handle/123456789/5546 http://dx.doi.org/10.1007/s11554-013-0338-1 |
url |
http://repositorio.inesctec.pt/handle/123456789/5546 http://dx.doi.org/10.1007/s11554-013-0338-1 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799131603377586176 |